Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data

In data fitting, researchers use various methods to determine the quality of a fitting. Visualization of images is crucial in observing the behavior of data obtained. The problem in judging the accuracy of a result obtained through visual observation are commonly faced by researchers when handling...

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Main Author: Sahubar Ali, Nur Soffiah
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:http://eprints.usm.my/62877/
http://eprints.usm.my/62877/1/Pages%20from%20Nur%20Soffiah%20Sahubar%20Ali.pdf
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author Sahubar Ali, Nur Soffiah
author_facet Sahubar Ali, Nur Soffiah
author_sort Sahubar Ali, Nur Soffiah
building USM Institutional Repository
collection Online Access
description In data fitting, researchers use various methods to determine the quality of a fitting. Visualization of images is crucial in observing the behavior of data obtained. The problem in judging the accuracy of a result obtained through visual observation are commonly faced by researchers when handling contaminated data such as noisy data, missing data and outliers. In this research, study has been conducted to deal with those noisy data and missing data using least square titting (LSF).
first_indexed 2025-11-15T19:17:23Z
format Thesis
id usm-62877
institution Universiti Sains Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T19:17:23Z
publishDate 2019
recordtype eprints
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spelling usm-628772025-09-26T07:43:01Z http://eprints.usm.my/62877/ Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data Sahubar Ali, Nur Soffiah QA297-299.4 Numerical Analysis In data fitting, researchers use various methods to determine the quality of a fitting. Visualization of images is crucial in observing the behavior of data obtained. The problem in judging the accuracy of a result obtained through visual observation are commonly faced by researchers when handling contaminated data such as noisy data, missing data and outliers. In this research, study has been conducted to deal with those noisy data and missing data using least square titting (LSF). 2019-08 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/62877/1/Pages%20from%20Nur%20Soffiah%20Sahubar%20Ali.pdf Sahubar Ali, Nur Soffiah (2019) Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data. PhD thesis, Universiti Sains Malaysia.
spellingShingle QA297-299.4 Numerical Analysis
Sahubar Ali, Nur Soffiah
Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
title Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
title_full Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
title_fullStr Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
title_full_unstemmed Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
title_short Curve Fitting With Bootstrap Error Analysis And Its Application On Two-Dimensional Data
title_sort curve fitting with bootstrap error analysis and its application on two-dimensional data
topic QA297-299.4 Numerical Analysis
url http://eprints.usm.my/62877/
http://eprints.usm.my/62877/1/Pages%20from%20Nur%20Soffiah%20Sahubar%20Ali.pdf